Max Robotics — Global Service Robot Directory + US Certification

About

Mana Masuda is a rising researcher at the intersection of surgical robotics, computer vision, and extended reality (XR). Her work focuses on developing machine learning models to enhance robotic-assisted surgery and immersive 3D scene understanding. Masuda’s most cited paper, "Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025" (6 citations), demonstrates her leadership in advancing surgical data science by inviting the community to build algorithms for tool localization and video understanding in robotic surgery. She also pioneered the "Neural Implicit Event Generator for Motion Tracking" (3 citations), a novel framework that uses implicit neural representations to track motion from event data, enabling high-speed, low-latency tracking for dynamic environments. Her recent survey, "Radiance Fields in XR" (1 citation), explores how neural radiance fields and 3D Gaussian Splatting are transforming photorealistic view synthesis for XR applications, highlighting her forward-looking perspective. While her citation counts are modest, Masuda’s contributions are notable for their technical novelty and direct impact on real-world surgical and XR systems, positioning her as an emerging voice in applied AI for healthcare and immersive technologies.